| ID | 原文 | 译文 |
| 54137 | 这种采用搜索的方法完成众多脉冲的相参积累，必然会带来巨大的计算量，不利于雷达的实时检测。 | This kind of algorithm inevitably brings a huge amount of computation because of multi-dimension search, which is not conducive to real-time detection of radar. |
| 54138 | 针对这个问题，根据目标各运动参数之间搜索的独立性和雷达回波信号的存储特点及GRFT算法思路，提出一种基于图形处理器(GPU:Graphic Processing Unit)的GRFT算法，实现了高维搜索并行化问题，并采用通用并行计算架构(CUDA:Computer Unified Device Architecture)完成了GRFT算法的具体实现。 | To address this issue, a GRFT algorithm based on graphic processing unit(GPU) is proposed in this paper, which combines search independence between motion parameters, the storage of radar echo signal and idea of GRFT algorithm. Computer unified deceive architecture(CUDA) is adopted to realize this algorithm. |
| 54139 | 仿真结果表明：GRFT算法的计算速度在GPU平台上得到显著提高。 | Numerical simulation results show that the computing speed of GRFT algorithm is significantly improved on the GPU platform. |
| 54140 | 现有的多传感器多目标跟踪算法大都基于马尔科夫-贝叶斯模型，需要诸如目标运动、杂波、传感器检测概率等先验信息，但是在恶劣的环境中，这些先验信息不准确并导致目标跟踪精度下降。 | The existing multi-sensor multi-target tracking algorithms are mostly based on Markov-Bayes model, which requires prior information such as target motion, clutter, and sensor detection probability, but in harsh environments, these prior information are not accurate and lead to a decrease in target tracking accuracy. |
| 54141 | 为了解决该情况下的多目标跟踪问题，我们提出了一个高效的分布式多目标跟踪算法，该算法通过泛洪(Flooding)共识算法在分布式网络的传感器之间迭代的传输、共享各自的量测集信息，并通过改进的密度峰值聚类(Improved Density Peaks Clustering，IDPC)算法对量测集聚类， | To solve the MTT problem in such situation, we propose an efficient distributed multi-target tracking algorithm, which uses a flooding consensus algorithm to iteratively transmit and share the measurement set information between sensors in the distributed network, and cluster the measurement set through an Improved density peaks clustering(IDPC) algorithm. |
| 54142 | 聚类得到的簇的个数即目标的个数，簇的中心即目标的位置。 | The number of clusters obtained by clustering is the number of targets, and the center of the clusters is target's position. |
| 54143 | 我们将IDPC算法与前沿的分布式概率密度假设(probability density hypothesis，PHD)滤波器在三个场景中进行对比，实验结果证明了IDPC算法的有效性和可靠性。 | We compare the IDPC algorithm with cutting edge distributed probability density hypothesis(PHD) filters in three scenarios, the experimental results prove the effectiveness and reliability of the IDPC algorithm. |
| 54144 | 准确地估计小型旋翼无人机的微动参数对无人机的识别具有重要意义，针对小型旋翼无人机弱微动特征的提取问题，本文提出了RSP-CFD(Reassigned Spectrogram-Cadence Frequency Diagram，RSP-CFD)的特征提取方法。 | Accurately estimating the micro-motion parameters of micro-rotor UAV is of great significance for the identification of UAV. For the extraction of weak micro-motion features of micro-rotor UAV, the feature extraction method of RSP-CFD(Reassigned Spectrogram-Cadence Frequency Diagram, RSP-CFD) is proposed in this paper. |
| 54145 | 首先采用高分辨时频分析方法RSP分析旋翼无人机的微动特性， | First, the high-resolution time-frequency analysis method RSP is used to analyze the micro-motion characteristics of the rotor UAV, |
| 54146 | 其次在RSP的基础上利用CFD方法提取旋翼无人机的微动特征， | then on the basis of RSP, the micro-motion characteristics of the rotor UAV are extracted by CFD method, |